Model updating is a critical task in structural damage identification and is commonly performed using finite element models; however, refined finite element modeling often suffers from low computational efficiency. To address this issue, this paper proposes an efficient spectral element model for reinforced concrete (RC) T-beams. First, the governing displacement equations are derived using Hamilton’s principle, and the displacement field is transformed from the time domain to the frequency domain using the fast Fourier transform (FFT). Based on this formulation, a spectral element model for RC T-beams is established, and a nonlinear static analysis framework is developed. To verify the proposed model, experimental tests are conducted on an RC T-beam specimen, and corresponding numerical simulations are performed using a finite element model. Finally, structural damage identification based on model updating is carried out using the proposed spectral element model. The results show that the proposed approach requires only 34 spectral elements to complete the analysis, demonstrating significantly higher computational efficiency than the finite element model while maintaining fast convergence. Overall, the proposed spectral element model provides an efficient and reliable tool for structural health monitoring and damage identification through model updating.